About this role
Developing and implementing AI-powered applications by integrating trained machine learning models, APIs, and data pipelines into functional software products takes up the daily schedule. Engineers design, build, deploy, and maintain applied machine learning systems that power critical products and workflows across the financial platform. Octaura operates as a technology company transforming how large, least digitized markets like loans and CLOs operate by applying AI, real-time data, and modern software design.
Working closely with product managers, software engineers, and data teams helps solve meaningful business problems and introduce AI responsibly into mission-critical systems. Depending on experience level, engineers take full ownership of complex machine learning initiatives and help shape the internal architecture. Candidates who thrive here possess a strong background in software development alongside practical machine learning expertise.
What you will do
- Design, build, and maintain production-grade backend services that power machine learning capabilities using Java, Spring Boot, Kafka, Redis, PostgreSQL, and Redshift.
- Develop, train, evaluate, and deploy machine learning models using Python-based frameworks such as scikit-learn, PyTorch, or TensorFlow.
- Architect and implement Agentic AI systems including multi-agent workflows, tool-use pipelines, and orchestration framework integrations.
- Build and maintain data pipelines and feature engineering workflows to support model training and inference.
- Collaborate with data scientists, platform engineers, and product teams to translate business needs into technical solutions.
- Implement MLOps practices including versioning, monitoring, A/B testing, and automated retraining pipelines.
- Write clean, testable code and participate in regular code reviews.
What you need
- Hold at least two years of software engineering experience with strong proficiency in Java and Spring Boot.
- Demonstrate hands-on experience building event-driven systems using Apache Kafka.
- Show solid understanding of relational databases and data warehousing tools like PostgreSQL and Redshift.
- Possess at least two years of hands-on experience in artificial intelligence and machine learning development using Python.
- Show familiarity with core machine learning concepts, supervised and unsupervised learning, and feature engineering.
- Demonstrate understanding of large language models, generative AI concepts, retrieval-augmented generation architectures, and agentic AI patterns.
Benefits
- Competitive compensation and equity
- Flexible Paid Time Off
- Competitive Parental Leave
- Daily breakfast, coffee and snacks in the office
- 90% company-paid healthcare
- Onsite gym and discounted membership
Skills and tech stack
Questions candidates ask
What is the remote work policy?
This role is based out of the New York City office located at 5 Penn Plaza. Employees follow a hybrid schedule consisting of four days in the office from Monday through Thursday and one day working remotely on Friday.
What is the salary range for this position?
The base pay range for this position in New York is $130,000 to $160,000 annually. Actual pay may vary depending on job-related knowledge, skills, and experience.
What technologies will I be using daily?
The tech stack includes Java, Spring Boot, Apache Kafka, Redis, PostgreSQL, Redshift, and Python-based machine learning frameworks such as scikit-learn, PyTorch, and TensorFlow.
What additional compensation is included beyond base salary?
Equity and year-end bonuses may be provided as part of the compensation package. Employees also receive a full range of medical, financial, and other benefits depending on the position offered.